Computer Systems Lab TJHSST Current Projects InHouse, pt 6

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Computer Systems LabTJHSSTCurrent
ProjectsIn-House, pt 6
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Current Projects, pt. 6In-House

• Algorithms for Computational Comparative
  Historical Linguistics
• Optimizing Genetic Algorithms for Cypher Decoding
• Decision Trees for Career Guidance
• Archival of Articles via RSS and Datamining
  Performed on Stored Articles
• Sabermetric Statistics in Baseball

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Algorithms for Computational Comparative
Historical Linguistics Over time, languages
change by regular, systematic processes. It is
possible, by looking at the state of a language
now and in the past, to deduce the exact changes
that occurred, and the order in which they
occurred. These changes also split languages,
therefore it is also possible to, by using modern
languages as input, induce the probable structure
of their parent language. My goal is to develop
algorithms by which computers may efficiently
analyze the historical structure of languages and
language families.
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Optimizing Genetic Algorithms for Cypher
DecodingOver the past several years, genetic
algorithms have come into wide use because of
their ability to find good solutions to computing
problems very quickly. They imitate nature by
crossing over strings of information represented
as chromosomes, with preference given to the more
fit solutions produced. They hold great promise
in the field of cryptology, where they may be
used to quickly find good partial solutions, thus
eliminating much of the intense manual labor that
goes into identifying initial coding schemes.
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Decision Trees for Career GuidanceThis research
project will be an investigation into the design
and implementation of various decision trees for
career guidance. A decision tree takes into
account some sort of situation outlined by a
group of parameters and outputs a Boolean
decision to the situation. This project will take
into account many aspects associated with
decision trees including database building,
searching and sorting, and algorithms for
accessing data.My project utilizes numerous
decision trees in an effort to serve as a tool
for career guidance for young adults. A user will
fill out a form of specified fields that will
then be analyzed by the group of decision trees
until a field of study/occupation is given to the
user as the outcome. This group of decision trees
will be built through database building
techniques.
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Archival of Articles via RSS and Datamining
Performed on Stored ArticlesRSS (Really Simple
Syndication, encompassing Rich Site Summary and
RDF Site Summary) is a web syndication protocol
used by many blogs and news websites to
distribute information it saves people having to
visit several sites repeatedly to check fornew
content. At this point in time there are many RSS
newsfeed aggregators available to the public, but
none of them perform anysort of archival of
information beyond the RSS metadata. The purpose
of this project is to create an RSS aggregator
that will archive the text of the actual articles
linked toin the RSS feeds in some kind of
linkable, searchable database, and, if all goes
well, implement some sort of datamining
capabilityas well.
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An Analysis of Sabermetric Statistics in
BaseballFor years, baseball theorists have
pondered the most basic question of baseball
statistics which statistic most accurately
predicts which team will win a baseball game.
With this information, baseball teams can rely on
technological, statistical-based scouting
organizations. The book, Moneyball addresses the
advent of sabermetric statistics in the 1980s and
1990s and shows how radical baseball thinkers
instituted a new era of baseball scouting and
player analyzation. This project analyzes which
baseball statistic isthe single most important.
It has been found that new formulas, such as OBP,
OPS, and Runs Created correlate better with the
number of runs a team scores than traditional
statistics such as batting average.
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